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handling-outlier

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Muhammad-Sheraz-ds / 100Days-of-Machine-Learning

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Embark on a transformative "100 Days of Machine Learning" journey. This curated repository guides enthusiasts through a hands-on approach, covering fundamental ML concepts, algorithms, and applications. Each day, engage in theoretical insights, practical coding exercises, and real-world projects. Balance theory with hands-on experience.

reinforcement-learning exploratory-data-analysis models machine-learning-algorithms regression data-acquisition data-visualization feature-extraction supervised-learning classification feature-engineering unsupervised-learning evaluation-metrics clustering-algorithm time-series-analysis handling-missing-value handling-outlier business-problem data-preprocessing-and-cleaning
  • Updated Jun 28, 2024
  • Jupyter Notebook

anupamsaha18 / Fintech-Capstone-Project---Loan-Default-Analysis

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The Loan Default Analysis project aims to identify key factors contributing to loan defaults by analyzing borrower profiles, financial data, and credit risk indicators. Using statistical methods, visualizations, and predictive modeling, the project provides insights to mitigate risks and improve lending strategies.

sql eda tableau risk-assessment probability-and-statistics credit-risk-analysis python-pandas-recipes handling-missing-value python-scikit-optimize handling-outlier data-cleaning-and-preprocessing pandas-numpy-matplotlib-seaborn
  • Updated Mar 21, 2025
  • Jupyter Notebook

PoojaP-atil / Titanic-case-study

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* Basis EDA * Handling Null/Missing Values * Handling Outliers * Handling Skewness * Handling Categorical Features * Data Normalization and Scaling * Feature Engineering *Accuracy score *Confusion matrix *Classification report

heatmap eda confusion-matrix scaling feature-engineering data-normalization classification-report standarization accuracy-score handling-missing-value handling-outlier handling-categorical-values handling-skewness
  • Updated Jun 4, 2024
  • Jupyter Notebook

Adyy7902 / Restaurant-Success-Prediction

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👩🏻‍🍳🍽️Restaurant Success Prediction using ML

machine-learning data-visualization sqlite3 outlier-detection restaurant feature-engineering feature-importance random-forest-classifier feature-encoding distplot hypertuning one-hot-encoding wordcloud-visualization grid-search-cross-validation success-prediction handling-outlier histplot data-cleaning-and-preprocessing model-building-and-evaluation randomised-search-cross-validation
  • Updated Sep 21, 2024
  • Jupyter Notebook
Diabetes-Predection-using-Ensemble-Learning

sumaaan / Diabetes-Predection-using-Ensemble-Learning

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This research work summarized different machine learning algorithms to create models for predicting diabetes patients utilizing the Diabetes Dataset (PIDD) from the UCI repository. The classifiers were K-Nearest Neighbors, Naïve Bayes, Support Vector, Decision Tree, Random Forest, Logistic Regression and Ensemble Model using a voting classifier.

machine-learning random-forest svm naive-bayes-classifier ensemble-learning logistic-regression confusion-matrix decision-trees feature-engineering knn boxplot datavisualization voting-classifier roc-score streamlit-webapp confusion-matrix-heatmap auc-score handling-outlier
  • Updated Jan 8, 2023
  • Jupyter Notebook

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